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The Journal of Business Cycle Measurement and Analysis has been discontinued as of 24 June 2016. This journal was published jointly with CIRET from 2004 to 2015. For more information see www.ciret.org/jbcy.
We decompose variations in the aggregate exit rate from unemployment to employment into two factors: i) Changes in the arrival rate of acceptable job offers; and ii) changes in the composition of the unemployment pool in terms of average employability. We argue that the former of these factors provides the basis for an informative labour market tightness indicator, while the latter yields valuable information regarding the design of optimal labour market policies across the cycle. Based on Norwegian register data, we find that individual monthly exit rates tend to double from a cyclical trough to a cyclical peak, ceteris paribus, but that crosssectional heterogeneity nevertheless explains 88 per cent of the overall variation in individual monthly exit probabilities during the period from 1989 to 2002.
The paper looks at an often debated issue – the decline observed in business cycle volatility – using qualitative data derived from Business Tendency Surveys. It concentrates on the manufacturing sector, providing evidence that volatility slowdown is attributable to a break in the Data Generating Process (Cecchetti, Flores-Lagunes and Krause, 2006) rather than to a long trend decline (Blanchard and Simon, 2001). Moreover, it shows that lower variance of the ISAE Confidence Indicator is mostly explained by the behaviour of firms' assessments of demand and inventories. In particular, inventories volatility has decreased, while volatility of production has instead increased with respect to that of demand. Both of these results are consistent with the claim that better inventories management should have a specific role in shaping the production decisions of the firms (Wen, 2005).
This paper assesses the leading indicator properties of the Economic Sentiment Indicator (ESI) of the European Commission, as well as two of its subcomponents, for industrial production growth. For this purpose we perform correlation analysis, Granger causality tests, an assessment on the ability to predict turning points and an out-of-sample forecasting exercise. Within a panel setting we compare the characteristics of these indicators for two subgroups of EU countries: the EU-15 and the new EU member states. We show that the forecasting quality and the leading indicator properties are still slightly lagging behind in the group of new EU member states. This may be related to the general problem of data quality and the undergone history of structural change in these countries that makes the assessment of future economic prospects particularly difficult.
This paper evaluates the performances of Japanese leading indicators in predicting business cycle turning points. We extract the business cycle component in leading indicators using the frequency selective filter proposed by Baxter and King (1999), and we try to clarify empirically whether or not the leading composite index and its component series truly lead the business cycle turning point dates officially determined by the Japanese government. We argue that if we utilize the evaluated properties of the component series, we may construct a composite leading indicator which has some desirable properties as requested. As an illustration we provide one such example.
This paper presents a comprehensive analysis of the current period performance of the OECD composite leading indicators (CLIs) for 21 OECD Member countries and three zone aggregates for which CLIs are available for a longer time period. The main aim of the current analysis on CLIs is to further evaluate the quality of the indicator in order to identify areas where their reliability could be improved. The results show that first estimates of CLIs are revised frequently but the size of revisions is rather small for most countries and almost neglectable for zone aggregates and there is no evidence of bias. The OECD CLI is, however, designed to provide early signals of turning points (peaks and troughs) between expansions and slowdowns of economic activity. Forecasting turning points is one of the main objectives of the leading indicator technique, because predicting the timing of cyclical turning points is one of the least reliable activities in economic forecasting. The results provide evidence that first and second estimates of year-on-year growth rates give reliable signals of approaching cyclical turning points. Finally, the importance of smoothness of components in the calculation of first and second estimates of the CLI and the overall smoothness of the CLI itself is noted in the findings. The results support the argument that it is not enough to have timely components they also need to be smooth to guarantee small revisions. Overall, this study has shown that whilst it could be dangerous to draw conclusions on the directions up or down in growth rates from one or two months figures for several countries, the first and second estimates of the CLIs give early signals of approaching turning points which in most cases are not revised later.